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Autor:innen: 
Erscheinungsjahr: 
1988
Schriftenreihe/Nr.: 
Queen's Economics Department Working Paper No. 717
Verlag: 
Queen's University, Department of Economics, Kingston (Ontario)
Zusammenfassung: 
It is remarkably easy to test for structural change, of the type that the classic F or "Chow" test is designed to detect, in a manner that is robust to heteroskedasticity of possibly unknown form. This paper first discusses how to test for structural change in nonlinear regression models by using a variant of the Gauss-Newton regression. It then shows how to make these tests robust to heteroskedasticity of unknown form and discusses several related procedures for doing so. Finally, it presents the results of a number of Monte Carlo experiments designed to see how well the new tests perform in finite samples.
Schlagwörter: 
Chow test
HCCME
heteroskedasticity
artificial regression
Gauss-Newton regression
GNR
structural break
Dokumentart: 
Working Paper

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